Implications of confounding from unmodeled interactions between explanatory variables when using latent variable regression models to make inferences.

With linear dependency between the explanatory variables, partial least squares (PLS) regression is commonly used for regression analysis. If the response variable correlates to a high degree with the explanatory variables, a model with excellent predictive ability can usually be obtained. Ranking of variable importance is commonly used to interpret the model and sometimes this interpretation guides further experimentation. For instance, when analyzing natural product extracts for bioactivity, an underlying assumption is that the highest ranked compounds represent the best candidates for isolation and further testing. A problem with this approach is that in most cases the number of compounds is larger than the number of samples (and usually much larger) and that the concentrations of the compounds correlate. Furthermore, compounds may interact as synergists or as antagonists. If the modelling process does not account for this possibility, the interpretation can be thoroughly wrong since unmodelled variables that strongly influence the response will give rise to confounding of a first order PLS model and send the experimenter on a wrong track. We show the consequences of this by a practical example from natural product research. Furthermore, we show that by including the possibility of interactions between explanatory variables, visualization using a selectivity ratio plot may provide model interpretation that can be used to make inferences.

From plant to cancer drug: lessons learned from the discovery of taxol.

Many researchers in the natural product sciences dream of discovering a successful drug. For almost all of us, this dream will never be realized. Among the heroes of our past, though, there is a team whose efforts led to the discovery of not one but two new drugs. Dr Monroe Wall and Dr Mansukh Wani isolated and solved the structures for taxol and camptothecin, plant-based compounds that continue to play a critical role in cancer therapy today. Since the 1960s and 1970s when Wall, Wani and collaborators did their seminal work, there have been tremendous technological advances in the natural product sciences. With access to most sophisticated technology, it might be expected that the rate of discovery of new drugs from plants and other sources would have sped up. However, this has not come to pass. Why is this? Is it that the promise of new drug candidates from plant-based sources has been exhausted? Has our fascination with new technologies and with the promise of the genomics revolution caused us to stop investing effort and resources in the practices that are proven to yield success? With this Viewpoint, we share the story of taxol's discovery, highlighting critical challenges that were overcome and considering their relevance to botanical natural products drug discovery today. We hope that consideration of lessons learned from the past will help fuel success by researchers currently studying plants with the goal of discovering promising therapeutic leads.

Translating Kratom-Drug Interactions: From Bedside to Bench and Back.

Kratom is a botanical natural product belonging to the coffee family, with stimulant effects at low doses and opioid-like effects at higher doses. During the last two decades, kratom has been purported as a safer alternative to pharmaceutical and illicit drugs to self-manage pain and opioid withdrawal symptoms. Kratom alkaloids, typically mitragynine, have been detected in biologic samples from overdose deaths. These deaths are often observed in combination with other drugs and are suspected to result from polyintoxications. This review focuses on the potential for kratom to precipitate pharmacokinetic interactions with object drugs involved in these reported polyintoxications. The legal status, chemistry, pharmacology, and toxicology are also summarized. The aggregate in vitro and clinical data identified kratom and select kratom alkaloids as modulators of cytochrome P450 (P450) enzyme activity, notably as inhibitors of CYP2D6 and CYP3A, as well as P-glycoprotein-mediated efflux activity. These inhibitory effects could increase the systemic exposure to co-consumed object drugs, which may lead to adverse effects. Collectively, the evidence to date warrants further evaluation of potential kratom-drug interactions using an iterative approach involving additional mechanistic in vitro studies, well designed clinical studies, and physiologically based pharmacokinetic modeling and simulation. This critical information is needed to fill knowledge gaps regarding the safe and effective use of kratom, thereby addressing ongoing public health concerns. SIGNIFICANCE STATEMENT: The botanical kratom is increasingly used to self-manage pain and opioid withdrawal symptoms due to having opioid-like effects. The legal status, chemistry, pharmacology, toxicology, and drug interaction potential of kratom are reviewed. Kratom-associated polyintoxications and in vitro-in vivo extrapolations suggest that kratom can precipitate pharmacokinetic drug interactions by inhibiting CYP2D6, CYP3A, and P-glycoprotein. An iterative approach that includes clinical studies and physiologically based pharmacokinetic modeling and simulation is recommended for further evaluation of potential unwanted kratom-drug interactions.

Goldenseal-Mediated Inhibition of Intestinal Uptake Transporters Decreases Metformin Systemic Exposure in Mice.

Goldenseal is a perennial plant native to eastern North America. A recent clinical study reported goldenseal decreased metformin Cmax and area under the blood concentration versus time curve (AUC) by 27% and 23%, respectively, but half-life and renal clearance were unchanged. These observations suggested goldenseal altered processes involved in metformin absorption. The underlying mechanism(s) remain(s) unknown. One mechanism for the decreased metformin systemic exposure is inhibition by goldenseal of intestinal uptake transporters involved in metformin absorption. Goldenseal extract and three goldenseal alkaloids (berberine, (-)-ß-hydrastine, hydrastinine) were tested as inhibitors of organic cation transporter (OCT) 3, plasma membrane monoamine transporter (PMAT), and thiamine transporter (THTR) 2 using human embryonic kidney 293 cells overexpressing each transporter. The goldenseal extract, normalized to berberine content, was the strongest inhibitor of each transporter (IC50: 4.9, 13.1, and 5.8 µM for OCT3, PMAT, and THTR2, respectively). A pharmacokinetic study in mice compared the effects of berberine, (-)-ß-hydrastine, goldenseal extract, and imatinib (OCT inhibitor) on orally administered metformin. Goldenseal extract and imatinib significantly decreased metformin Cmax by 31% and 25%, respectively, and had no effect on half-life. Berberine and (-)-ß-hydrastine had no effect on metformin pharmacokinetics, indicating neither alkaloid alone precipitated the interaction in vivo. A follow-up murine study involving intravenous metformin and oral inhibitors examined the contributions of basolateral enteric/hepatic uptake transporters to the goldenseal-metformin interaction. Goldenseal extract and imatinib had no effect on metformin AUC and half-life, suggesting lack of inhibition of basolateral enteric/hepatic uptake transporters. Results may have implications for patients taking goldenseal with drugs that are substrates for OCT3 and THTR2. SIGNIFICANCE STATEMENT: Goldenseal is used to self-treat respiratory infections and digestive disorders. We investigated potential mechanisms for the clinical pharmacokinetic interaction observed between goldenseal and metformin, specifically inhibition by goldenseal of intestinal uptake transporters (OCT3, PMAT, THTR2) involved in metformin absorption. Goldenseal extract inhibited all three transporters in vitro and decreased metformin systemic exposure in mice. These data may have broader implications for patients co-consuming goldenseal with other drugs that are substrates for these transporters.

Interaction Metabolomics to Discover Synergists in Natural Product Mixtures.

Mass spectrometry metabolomics has become increasingly popular as an integral aspect of studies to identify active compounds from natural product mixtures. Classical metabolomics data analysis approaches do not consider the possibility that interactions (such as synergy) could occur between mixture components. With this study, we developed "interaction metabolomics" to overcome this limitation. The innovation of interaction metabolomics is the inclusion of compound interaction terms (CITs), which are calculated as the product of the intensities of each pair of features (detected ions) in the data matrix. Herein, we tested the utility of interaction metabolomics by spiking known concentrations of an antimicrobial compound (berberine) and a synergist (piperine) into a set of inactive matrices. We measured the antimicrobial activity for each of the resulting mixtures against Staphylococcus aureus and analyzed the mixtures with liquid chromatography coupled to high-resolution mass spectrometry. When the data set was processed without CITs (classical metabolomics), statistical analysis yielded a pattern of false positives. However, interaction metabolomics correctly identified berberine and piperine as the compounds responsible for the synergistic activity. To further validate the interaction metabolomics approach, we prepared mixtures from extracts of goldenseal (Hydrastis canadensis) and habañero pepper (Capsicum chinense) and correctly correlated synergistic activity of these mixtures to the combined action of berberine and several capsaicinoids. Our results demonstrate the utility of a conceptually new approach for identifying synergists in mixtures that may be useful for applications in natural products research and other research areas that require comprehensive mixture analysis.

Modulation of in Vitro SARS-CoV-2 Infection by Stephania tetrandra and Its Alkaloid Constituents.

Botanical natural products have been widely consumed for their purported usefulness against COVID-19. Here, six botanical species from multiple sources and 173 isolated natural product compounds were screened for blockade of wild-type (WT) SARS-CoV-2 infection in human 293T epithelial cells overexpressing ACE-2 and TMPRSS2 protease (293TAT). Antiviral activity was demonstrated by an extract from Stephania tetrandra. Extract fractionation, liquid chromatography-mass spectrometry (LC-MS), antiviral assays, and computational analyses revealed that the alkaloid fraction and purified alkaloids tetrandrine, fangchinoline, and cepharanthine inhibited WT SARS-CoV-2 infection. The alkaloids and alkaloid fraction also inhibited the delta variant of concern but not WT SARS-CoV-2 in VeroAT cells. Membrane permeability assays demonstrate that the alkaloids are biologically available, although fangchinoline showed lower permeability than tetrandrine. At high concentrations, the extract, alkaloid fractions, and pure alkaloids induced phospholipidosis in 293TAT cells and less so in VeroAT cells. Gene expression profiling during virus infection suggested that alkaloid fraction and tetrandrine displayed similar effects on cellular gene expression and pathways, while fangchinoline showed distinct effects on cells. Our study demonstrates a multifaceted approach to systematically investigate the diverse activities conferred by complex botanical mixtures, their cell-context specificity, and their pleiotropic effects on biological systems.

How Low Can You Go? Selecting Intensity Thresholds for Untargeted Metabolomics Data Preprocessing.

Untargeted mass spectrometry (MS) metabolomics is an increasingly popular approach for characterizing complex mixtures. Recent studies have highlighted the impact of data preprocessing for determining the quality of metabolomics data analysis. The first step in data processing with untargeted metabolomics requires that signal thresholds be selected for which features (detected ions) are included in the dataset. Analysts face the challenge of knowing where to set these thresholds; setting them too high could mean missing relevant features, but setting them too low could result in a complex and unwieldy dataset. This study compared data interpretation for an example metabolomics dataset when intensity thresholds were set at a range of feature heights. The main observations were that low signal thresholds (1) improved the limit of detection, (2) increased the number of features detected with an associated isotope pattern and/or an MS-MS fragmentation spectrum, and (3) increased the number of in-source clusters and fragments detected for known analytes of interest. When the settings of parameters differing in intensities were applied on a set of 39 samples to discriminate the samples through principal component analyses (PCA), similar results were obtained with both low- and high-intensity thresholds. We conclude that the most information-rich datasets can be obtained by setting low-intensity thresholds. However, in the cases where only a qualitative comparison of samples with PCA is to be performed, it may be sufficient to set high thresholds and thereby reduce the complexity of the data processing and amount of computational time required.

Chalcones from Angelica keiskei (ashitaba) inhibit key Zika virus replication proteins.

Zika virus (ZIKV) is a dangerous human pathogen and no antiviral drugs have been approved to date. The chalcones are a group of small molecules that are found in a number of different plants, including Angelica keiskei Koidzumi, also known as ashitaba. To examine chalcone anti-ZIKV activity, three chalcones, 4-hydroxyderricin (4HD), xanthoangelol (XA), and xanthoangelol-E (XA-E), were purified from a methanol-ethyl acetate extract from A. keiskei. Molecular and ensemble docking predicted that these chalcones would establish multiple interactions with residues in the catalytic and allosteric sites of ZIKV NS2B-NS3 protease, and in the allosteric site of the NS5 RNA-dependent RNA-polymerase (RdRp). Machine learning models also predicted 4HD, XA and XA-E as potential anti-ZIKV inhibitors. Enzymatic and kinetic assays confirmed chalcone inhibition of the ZIKV NS2B-NS3 protease allosteric site with IC50s from 18 to 50 µM. Activity assays also revealed that XA, but not 4HD or XA-E, inhibited the allosteric site of the RdRp, with an IC50 of 6.9 µM. Finally, we tested these chalcones for their anti-viral activity in vitro with Vero cells. 4HD and XA-E displayed anti-ZIKV activity with EC50 values of 6.6 and 22.0 µM, respectively, while XA displayed relatively weak anti-ZIKV activity with whole cells. With their simple structures and relative ease of modification, the chalcones represent attractive candidates for hit-to-lead optimization in the search of new anti-ZIKV therapeutics.

More Than Just a Weed: An Exploration of the Antimicrobial Activity of Rumex crispus using a Multivariate Data Analysis Approach.

Plants have a long history of use for their medicinal properties. The complexity of botanical extracts presents unique challenges and necessitates the application of innovative approaches to correctly identify and quantify bioactive compounds. For this study, we used untargeted metabolomics to explore the antimicrobial activity of Rumex crispus (yellow dock), a member of the Polygonaceae family used as an herbal remedy for bacterial infections. Ultra-performance liquid chromatography coupled with high resolution mass-spectrometry (UPLC-MS) was used to identify and quantify the known antimicrobial compound emodin. In addition, we used biochemometric approaches to integrate data measuring antimicrobial activity from R. crispus root starting material and fractions against methicillin-resistant Staphylococcus aureus (MRSA) with UPLC-MS data. Our results support the hypothesis that multiple constituents, including the anthraquinone emodin, contribute to the antimicrobial activity of R. crispus against MRSA.

Kratom (Mitragyna speciosa) Validation: Quantitative Analysis of Indole and Oxindole Alkaloids Reveals Chemotypes of Plants and Products.

Many consumers are turning to kratom (Mitragyna speciosa) to self-manage pain and opioid addiction. In the United States, an array of capsules, powders, and loose-leaf kratom products are readily available. Additionally, several online sites supply live kratom plants. A prerequisite to establishing quality control and quality assurance standards for the kratom industry, or understanding how alkaloid levels effect clinical outcomes, is the identification and quantitation of major and minor alkaloid constituents within available products and preparations. To this end, an ultra-high performance liquid chromatography-high resolution mass spectrometry method was developed for the analysis of 8 indole alkaloids (7-hydroxymitragynine, ajmalicine, paynantheine, mitragynine, speciogynine, isopaynantheine, speciociliatine, and mitraciliatine) and 6 oxindole alkaloids (isomitraphylline, isospeciofoleine, speciofoline, corynoxine A, corynoxeine, and rhynchophylline) in US-grown kratom plants and commercial products. These commercial products shared a qualitatively similar alkaloid profile, with 12 - 13 detected alkaloids and high levels of the indole alkaloid mitragynine (13.9 ± 1.1 - 270 ± 24 mg/g). The levels of the other major alkaloids (paynantheine, speciociliatine, speciogynine, mitraciliatine, and isopaynantheine) and the minor alkaloids varied in concentration from product to product. The alkaloid profile of US-grown M. speciosa "Rifat" showed high levels of the indole alkaloid speciogynine (7.94 ± 0.83 - 11.55 ± 0.18 mg/g) and quantifiable levels of isomitraphylline (0.943 ± 0.033 - 1.47 ± 0.18 mg/g). Notably, the alkaloid profile of a US-grown M. speciosa seedling was comparable to the commercial products with a high level of mitragynine (15.01 ± 0.20 mg/g). This work suggests that there are several M. speciosa chemotypes.

Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality.

Systematic, large-scale, studies at the genomic, metabolomic, and functional level have transformed the natural product sciences. Improvements in technology and reduction in cost for obtaining spectroscopic, chromatographic, and genomic data coupled with the creation of readily accessible curated and functionally annotated data sets have altered the practices of virtually all natural product research laboratories. Gone are the days when the natural products researchers were expected to devote themselves exclusively to the isolation, purification, and structure elucidation of small molecules. We now also engage with big data in taxonomic, genomic, proteomic, and/or metabolomic collections, and use these data to generate and test hypotheses. While the oft stated aim for the use of large-scale -omics data in the natural products sciences is to achieve a rapid increase in the rate of discovery of new drugs, this has not yet come to pass. At the same time, new technologies have provided unexpected opportunities for natural products chemists to ask and answer new and different questions. With this viewpoint, we discuss the evolution of big data as a part of natural products research and provide a few examples of how discoveries have been enabled by access to big data. We also draw attention to some of the limitations in our existing engagement with large datasets and consider what would be necessary to overcome them.

Refined Prediction of Pharmacokinetic Kratom-Drug Interactions: Time-Dependent Inhibition Considerations.

Preparations from the leaves of the kratom plant (Mitragyna speciosa) are consumed for their opioid-like effects. Several deaths have been associated with kratom used concomitantly with some drugs. Pharmacokinetic interactions are potential underlying mechanisms of these fatalities. Accumulating in vitro evidence has demonstrated select kratom alkaloids, including the abundant indole alkaloid mitragynine, as reversible inhibitors of several cytochromes P450 (CYPs). The objective of this work was to refine the mechanistic understanding of potential kratom-drug interactions by considering both reversible and time-dependent inhibition (TDI) of CYPs in the liver and intestine. Mitragynine was tested against CYP2C9 (diclofenac 4'-hydroxylation), CYP2D6 (dextromethorphan O-demethylation), and CYP3A (midazolam 1'-hydroxylation) activities in human liver microsomes (HLMs) and CYP3A activity in human intestinal microsomes (HIMs). Comparing the absence to presence of NADPH during preincubation of mitragynine with HLMs or HIMs, an ∼7-fold leftward shift in IC50 (∼20 to 3 µM) toward CYP3A resulted, prompting determination of TDI parameters (HLMs: K I , 4.1 ± 0.9 µM; k inact , 0.068 ± 0.01 min-1; HIMs: K I , 4.2 ± 2.5 µM; k inact , 0.079 ± 0.02 min-1). Mitragynine caused no leftward shift in IC50 toward CYP2C9 (∼40 µM) and CYP2D6 (∼1 µM) but was a strong competitive inhibitor of CYP2D6 (K i , 1.17 ± 0.07 µM). Using a recommended mechanistic static model, mitragynine (2-g kratom dose) was predicted to increase dextromethorphan and midazolam area under the plasma concentration-time curve by 1.06- and 5.69-fold, respectively. The predicted midazolam area under the plasma concentration-time curve ratio exceeded the recommended cutoff (1.25), which would have been missed if TDI was not considered. SIGNIFICANCE STATEMENT: Kratom, a botanical natural product increasingly consumed for its opioid-like effects, may precipitate potentially serious pharmacokinetic interactions with drugs. The abundant kratom indole alkaloid mitragynine was shown to be a time-dependent inhibitor of hepatic and intestinal cytochrome P450 3A activity. A mechanistic static model predicted mitragynine to increase systemic exposure to the probe drug substrate midazolam by 5.7-fold, necessitating further evaluation via dynamic models and clinical assessment to advance the understanding of consumer safety associated with kratom use.

Interlaboratory Comparison of Untargeted Mass Spectrometry Data Uncovers Underlying Causes for Variability.

Despite the value of mass spectrometry in modern natural products discovery workflows, it remains very difficult to compare data sets between laboratories. In this study we compared mass spectrometry data for the same sample set from two different laboratories (quadrupole time-of-flight and quadrupole-Orbitrap) and evaluated the similarity between these two data sets in terms of both mass spectrometry features and their ability to describe the chemical composition of the sample set. Somewhat surprisingly, the two data sets, collected with appropriate controls and replication, had very low feature overlap (25.7% of Laboratory A features overlapping 21.8% of Laboratory B features). Our data clearly demonstrate that differences in fragmentation, charge state, and adduct formation in the ionization source are a major underlying cause for these differences. Consistent with other recent literature, these findings challenge the conventional wisdom that electrospray ionization mass spectrometry (ESI-MS) yields a simple one-to-one correspondence between analytes in solution and features in the data set. Importantly, despite low overlap in feature lists, principal component analysis (PCA) generated qualitatively similar PCA plots. Overall, our findings demonstrate that comparing untargeted metabolomics data between laboratories is challenging, but that data sets with low feature overlap can yield the same qualitative description of a sample set using PCA.

Novel Peptide from Commensal Staphylococcus simulans Blocks Methicillin-Resistant Staphylococcus aureus Quorum Sensing and Protects Host Skin from Damage.

Recent studies highlight the abundance of commensal coagulase-negative staphylococci (CoNS) on healthy skin. Evidence suggests that CoNS actively shape the skin immunological and microbial milieu to resist colonization or infection by opportunistic pathogens, including methicillin-resistant Staphylococcus aureus (MRSA), in a variety of mechanisms collectively termed colonization resistance. One potential colonization resistance mechanism is the application of quorum sensing, also called the accessory gene regulator (agr) system, which is ubiquitous among staphylococci. Common and rare CoNS make autoinducing peptides (AIPs) that function as MRSA agr inhibitors, protecting the host from invasive infection. In a screen of CoNS spent media, we found that Staphylococcus simulans, a rare human skin colonizer and frequent livestock colonizer, released potent inhibitors of all classes of MRSA agr signaling. We identified three S. simulans agr classes and have shown intraspecies cross talk between noncognate S. simulans agr types for the first time. The S. simulans AIP-I structure was confirmed, and the novel AIP-II and AIP-III structures were solved via mass spectrometry. Synthetic S. simulans AIPs inhibited MRSA agr signaling with nanomolar potency. S. simulans in competition with MRSA reduced dermonecrotic and epicutaneous skin injury in murine models. The addition of synthetic AIP-I also effectively reduced MRSA dermonecrosis and epicutaneous skin injury in murine models. These results demonstrate potent anti-MRSA quorum sensing inhibition by a rare human skin commensal and suggest that cross talk between CoNS and MRSA may be important in maintaining healthy skin homeostasis and preventing MRSA skin damage during colonization or acute infection.

Identification of adulteration in botanical samples with untargeted metabolomics.

Adulteration remains an issue in the dietary supplement industry, including botanical supplements. While it is common to employ a targeted analysis to detect known adulterants, this is difficult when little is known about the sample set. With this study, untargeted metabolomics using liquid chromatography coupled to ultraviolet-visible spectroscopy (LC-UV) or high-resolution mass spectrometry (LC-MS) was employed to detect adulteration in botanical dietary supplements. A training set was prepared by combining Hydrastis canadensis L. with a known adulterant, Coptis chinensis Franch., in ratios ranging from 5 to 95% adulteration. The metabolomics datasets were analyzed using both unsupervised (principal component analysis and composite score) and supervised (SIMCA) techniques. Palmatine, a known H. canadensis metabolite, was quantified as a targeted analysis comparison. While the targeted analysis was the most sensitive method tested in detecting adulteration, statistical analyses of the untargeted metabolomics datasets detected adulteration of the goldenseal samples, with SIMCA providing the greatest discriminating potential. Graphical abstract.

The Chemistry of Kratom [Mitragyna speciosa]: Updated Characterization Data and Methods to Elucidate Indole and Oxindole Alkaloids.

Two separate commercial products of kratom [Mitragyna speciosa (Korth.) Havil. Rubiaceae] were used to generate reference standards of its indole and oxindole alkaloids. While kratom has been studied for over a century, the characterization data in the literature for many of the alkaloids are either incomplete or inconsistent with modern standards. As such, full 1H and 13C NMR spectra, along with HRESIMS and ECD data, are reported for alkaloids 1-19. Of these, four new alkaloids (7, 11, 17, and 18) were characterized using 2D NMR data, and the absolute configurations of 7, 17, and 18 were established by comparison of experimental and calculated ECD spectra. The absolute configuration for the N(4)-oxide (11) was established by comparison of NMR and ECD spectra of its reduced product with those for compound 7. In total, 19 alkaloids were characterized, including the indole alkaloid mitragynine (1) and its diastereoisomers speciociliatine (2), speciogynine (3), and mitraciliatine (4); the indole alkaloid paynantheine (5) and its diastereoisomers isopaynantheine (6) and epiallo-isopaynantheine (7); the N(4)-oxides mitragynine-N(4)-oxide (8), speciociliatine-N(4)-oxide (9), isopaynantheine-N(4)-oxide (10), and epiallo-isopaynantheine-N(4)-oxide (11); the 9-hydroxylated oxindole alkaloids speciofoline (12), isorotundifoleine (13), and isospeciofoleine (14); and the 9-unsubstituted oxindoles corynoxine A (15), corynoxine B (16), 3-epirhynchophylline (17), 3-epicorynoxine B (18), and corynoxeine (19). With the ability to analyze the spectroscopic data of all of these compounds concomitantly, a decision tree was developed to differentiate these kratom alkaloids based on a few key chemical shifts in the 1H and/or 13C NMR spectra.

Chemical Evaluation of the Effects of Storage Conditions on the Botanical Goldenseal using Marker-based and Metabolomics Approaches.

Hydrastis canadensis, commonly known as goldenseal, is a botanical native to the southeastern United States that has been used for the treatment of infection. The activity of goldenseal is often attributed to the presence of alkaloids (cyclic, nitrogen-containing compounds) present within its roots. Chemical components of botanical supplements like goldenseal may face degradation if not stored properly. The purpose of the research was to analyze the stability of known and unknown metabolites of H. canadensis during exposure to different storage conditions using mass spectrometry. Three abundant metabolites of H. canadensis, berberine, canadine, and hydrastine, were chosen for targeted analysis, and the stability of unknown metabolites was evaluated using untargeted metabolomics. The analysis and evaluation of H. canadensis samples were performed utilizing LC-MS and Principal Component Analysis (PCA). The research project focused on identifying the chemical changes in the metabolite content of H. canadensis under different temperature conditions (40°C ± 5°C, 20°C ± 5°C , and 4°C ± 5°C), different light:dark (hr:hr) cycles (16:8, 12:12, and 0:24), and different sample conditions (powdered roots versus whole roots) over a six month period. The results of this 6-month study revealed that the storage conditions evaluated had no significant effects on the chemical composition of H. canadensis roots. Hence, as long as H. canadensis roots are stored within the storage conditions tested in the study, no significant changes in chemical compositions of metabolites are expected.

MroQ Is a Novel Abi-Domain Protein That Influences Virulence Gene Expression in Staphylococcus aureus via Modulation of Agr Activity.

Numerous factors have, to date, been identified as playing a role in the regulation of Agr activity in Staphylococcus aureus, including transcription factors, antisense RNAs, and host elements. Herein we investigated the product of SAUSA300_1984 (termed MroQ), a transmembrane Abi-domain/M79 protease-family protein, as a novel effector of this system. Using a USA300 mroQ mutant, we observed a drastic reduction in proteolysis, hemolysis, and pigmentation that was fully complementable. This appears to result from diminished agr activity, as transcriptional analysis revealed significant decreases in expression of both RNAII and RNAIII in the mroQ mutant. Such effects appear to be direct, rather than indirect, as known agr effectors demonstrated limited alterations in their activity upon mroQ disruption. A comparison of RNA sequencing data sets for both mroQ and agr mutants revealed a profound overlap in their regulomes, with the majority of factors affected being known virulence determinants. Importantly, the preponderance of alterations in expression were more striking in the agr mutant, indicating that MroQ is necessary, but not sufficient, for Agr function. Mechanism profiling revealed that putative residues for metalloprotease activity within MroQ are required for its Agr-controlling effect; however, this was not wielded at the level of AgrD processing. Virulence assessment demonstrated that both mroQ and agr mutants exhibited increased formation of renal abscesses but decreased skin abscess formation alongside diminished dermonecrosis. Collectively, we present the characterization of a novel agr effector in S. aureus which would appear to be a direct regulator, potentially functioning via interaction with the AgrC histidine kinase.

Synergy and antagonism in natural product extracts: when 1 + 1 does not equal 2.

Covering: 2000 to 2019 According to a 2012 survey from the Centers for Disease Control and Prevention, approximately 18% of the U.S. population uses natural products (including plant-based or botanical preparations) for treatment or prevention of disease. The use of plant-based medicines is even more prevalent in developing countries, where for many they constitute the primary health care modality. Proponents of the medicinal use of natural product mixtures often claim that they are more effective than purified compounds due to beneficial "synergistic" interactions. A less-discussed phenomenon, antagonism, in which effects of active constituents are masked by other compounds in a complex mixture, also occurs in natural product mixtures. Synergy and antagonism are notoriously difficult to study in a rigorous fashion, particularly given that natural products chemistry research methodology is typically devoted to reducing complexity and identifying single active constituents for drug development. This report represents a critical review with commentary about the current state of the scientific literature as it relates to studying combination effects (including both synergy and antagonism) in natural product extracts. We provide particular emphasis on analytical and Big Data approaches for identifying synergistic or antagonistic combinations and elucidating the mechanisms that underlie their interactions. Specific case studies of botanicals in which synergistic interactions have been documented are also discussed. The topic of synergy is important given that consumer use of botanical natural products and associated safety concerns continue to garner attention by the public and the media. Guidance by the natural products community is needed to provide strategies for effective evaluation of safety and toxicity of botanical mixtures and to drive discovery in botanical natural product research.

Selection and characterization of botanical natural products for research studies: a NaPDI center recommended approach.

Covering: up to the end of 2018 Dietary supplements, which include botanical (plant-based) natural products, constitute a multi-billion-dollar industry in the US. Regulation and quality control for this industry is an ongoing challenge. While there is general agreement that rigorous scientific studies are needed to evaluate the safety and efficacy of botanical natural products used by consumers, researchers conducting such studies face a unique set of challenges. Botanical natural products are inherently complex mixtures, with composition that differs depending on myriad factors including variability in genetics, cultivation conditions, and processing methods. Unfortunately, many studies of botanical natural products are carried out with poorly characterized study material, such that the results are irreproducible and difficult to interpret. This review provides recommended approaches for addressing the critical questions that researchers must address prior to in vitro or in vivo (including clinical) evaluation of botanical natural products. We describe selection and authentication of botanical material and identification of key biologically active compounds, and compare state-of-the-art methodologies such as untargeted metabolomics with more traditional targeted methods of characterization. The topics are chosen to be of maximal relevance to researchers, and are reviewed critically with commentary as to which approaches are most practical and useful and what common pitfalls should be avoided.